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4. Classification
4.1 Objectives
As in the case of multidimensional positioning (MDS), the data, which concern n individuals assigned, for simplicity, the same weight, can be presented in different forms:
a table of distances or measures of dissimilarity, n x n, between individuals taken in pairs;
the observations of p quantitative variables on these n individuals associated with a choice of metric ;
observations, always on these n individuals, of qualitative variables or a mixture of quantitative and qualitative variables.
In one way or another, in each case, it's a matter of returning to the table of pairwise distances between individuals (i.e. the first case). Choosing...
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Classification
Conclusion
Bibliography
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Other resources (handouts, practical exercises, functions written in R) are available on the website :
https://www.math.univ-toulouse.fr/
R Development Core TeamR: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing
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The most useful general and introductory references for this theme are: Bouroche & Saporta (1980), Jobson (1992), Lebart, Morineau & Piron (2006), Mardia, Kent & Bibby (1979), Saporta (2006). More recent additions and developments can be found in: Droesbeke, Fichet & Tassi (1992), Govaert (2003).
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